Inequality of opportunity in selection procedures limits diversity in higher education: An intersectional study of Dutch selective higher education programs

group ALL divided by that of group NONE) shows the contrast in opportunities for the groups that differed the most from each other. To provide insight into the acceptance rates of appli- cants who had some, but not all, of the characteristics positively associated with odds of admis- sion, we created figures which showcase these rates for every combination of characteristics. All analyses were performed using IBM SPSS software for Windows, Version 25.0 (IBM Corp, Armonk, NY). Results Representativeness S3 Table summarizes the demographic data of all applicants who received a ranking number, all applicants who were offered a seat in the program, and all those who became registered stu- dents, for each cluster. With these results, we can answer research question 1, on how repre- sentative student populations of selective HE programs are, compared to: a) the applicant pool; b) the higher general population and pre-university population; and c) their age cohort. Due to the extensive amount of descriptive statistics, we focus here on the variables with the largest differences between categories. Sex. The results show that when student populations are not representative of their age cohort or the higher general/pre-university population, this is partially due to self-selection in applications. For example, in SH1 (healthcare related), men constituted 13–14.5% of the stu- dent population in 2019, respectively 2020. This is primarily due to them applying in lower numbers (approximately 16% of the applicant pool). Most clusters in which men are underrep-

resented, concern health professions education programs. SU7 (mostly consisting of engineer- ing programs) was the only cluster in which women were significantly underrepresented: they made up 28–33% of the student population, but also only 28–31% of the applicant pool. Table 2. (Continued) Variable Values Rationale Number of parents who receive social welfare 0, 1, 2, recoded in 2 categories to create groups of sufficient size for logistic regression analysis: The low disposable income of families on social welfare, and the lack of a current network in the workforce, are hypothesized to have a negative effect on the child’s opportunity to enter a selective program. 0 = 0 parents 1 = 1 or 2 parents Number of parents who receive a social services income (excl. social welfare) 0, 1, 2, recoded in 2 categories to create groups of sufficient size for logistic regression analysis: There are different types of social services income, including types that are based on long-term illness or a labor disability. Combined with the lack of a current network in the workforce, these factors are hypothesized to have a negative effect on the child’s opportunity to enter a selective program. 0 = 0 parents 1 = 1 or 2 parents Number of parents who are registered healthcare professionals 0, 1, 2, recoded in 2 categories to create groups of sufficient size for logistic regression analysis: The known influence of having a network in the medical field as a facilitator in preparing for selection in health professions education programs [15, 16, 51–53] 0 = 0 parents 1 = 1 or 2 parents

Number of parents who work in the primary, secondary or vocational education sector 0, 1, 2, recoded in 2 categories to create groups of sufficient size for logistic regression analysis: We hypothesized that parents who work in the primary, secondary or vocational education sector can provide access to information about higher education and selection procedures. 0 = 0 parents 1 = 1 or 2 parents a It is acknowledged that not every individual is, or identifies as, ‘male’ or ‘female’, but Statistics Netherlands only has two possible sex categories. This means that e.g. intersex persons either have missing data on their sex registration, or are categorized as male or female. Transgender persons who have changed their sex registration in the national Personal Records Database are included in this study according to the sex which was registered in 2021. b When parents live in different households, they may each have a different household assets percentile. In that case, we selected the highest percentile. https://doi.org/10.1371/journal.pone.0292805.t002 PLOS ONE Inequality of opportunity in Dutch selection procedures limits diversity in higher education PLOS ONE | https://doi.org/10.1371/journal.pone.0292805 October 13, 2023 10 / 24